Biblio

In this paper, we deal with the resilient consensus problem in networked control systems in which a group of agents are interacting with each other. A min-max-based resilient consensus algorithm has been proposed to help normal agents reach an agreement upon their state values in the presence of misbehaving ones. It is shown that the use of the developed algorithm will result in less computational load and fast convergence. Both synchronous and asynchronous update schemes for the network have been studied. Finally, the effectiveness of the proposed algorithm has been evaluated through numerical examples.

Security in the communication systems rely mainly on a trusted Public Key Infrastructure (PKI) and Certificate Authorities (CAs). Besides the lack of automation, the complexity and the cost of assigning a signed certificate to a device, several allegations against CAs have been discovered, which has created trust issues in adopting this standard model for secure systems. The automation of the servers certificate assignment was achieved by the Automated Certificate Management Environment (ACME) method, but without confirming the trust of assigned certificate. This paper presents a complete tested and implemented solution to solve the trust of the Certificates provided to the servers by using the blockchain platform for certificate validation. The Blockchain network provides an immutable data store, holding the public keys of all domain names, while resolving the trust concerns by applying an automated Blockchain-based Domain Control Validation (B-DCV) for the server and client server verification. The evaluation was performed on the Ethereum Rinkeby testnet adopting the Proof of Authority (PoA) consensus algorithm which is an improved version of Proof of Stake (Po \$S\$) applied on Ethereum 2.0 providing superior performance compared to Ethereum 1.0.

Swarm robotics is a network based multi-device system designed to achieve shared objectives in a synchronized way. This system is widely used in industries like farming, manufacturing, and defense applications. In recent implementations, swarm robotics is integrated with Blockchain based networks to enhance communication, security, and decentralized decision-making capabilities. As most of the current blockchain applications are based on complex consensus algorithms, every individual robot in the swarm network requires high computing power to run these complex algorithms. Thus, it is a challenging task to achieve consensus between the robots in the network. This paper will discuss the details of designing an effective consensus algorithm that meets the requirements of swarm robotics network.

Blockchain started with Bitcoin, but it is higher than Bitcoin. With the deepening of applied research on blockchain technology, this new technology has brought new vitality to many industries. People admire the decentralized nature of the blockchain and hope to solve the problems caused by the operation of traditional centralized institutions in a more fair and effective way. Of course, as an emerging technology, blockchain has many areas for improvement. This article explains the blockchain technology from many aspects. Starting from the typical architecture of the blockchain, the data structure and system model of the blockchain are first introduced. Then it expounds the development of consensus algorithms and compares typical consensus algorithms. Later, the focus will be on smart contracts and their application platforms. After analyzing some of the challenges currently faced by the blockchain technology, some scenarios where the blockchain is currently developing well are listed. Finally, it summarizes and looks forward to the blockchain technology.

The limited spectrum resources need to provide safe and efficient spectrum service for the intensive users. Malicious spectrum work nodes will affect the normal operation of the entire system. Using the blockchain model, consensus algorithm Praft based on optimized Raft is to solve the consensus problem in Byzantine environment. Message digital signatures give the spectrum node some fault tolerance and tamper resistance. Spectrum sharing among spectrum nodes is carried out in combination with game theory. The existing game theoretical algorithm does not consider the influence of spectrum occupancy of primary users and cognitive users on primary users' utility and enthusiasm at the same time. We elicits a reinforcement factor and analyzes the effect of the reinforcement factor on strategy performance. This scheme optimizes the previous strategy so that the profits of spectrum nodes are improved and a good Nash equilibrium is shown, while Praft solves the Byzantine problem left by Raft.

Traditional grid-centric data storage methods are vulnerable to network attacks or failures due to downtime, causing problems such as data loss or tampering. The security of data storage can be effectively improved by establishing an alliance chain. However, the existing consortium chain consensus algorithm has low scalability, and the consensus time will explode as the number of nodes increases. This paper proposes an improved consensus algorithm (MSBFT) based on multi-signature to address this problem, which spreads data by establishing a system communication tree, reducing communication and network transmission costs, and improving system scalability. By generating schnorr multi-signature as the shared signature of system nodes, the computational cost of verification between nodes is reduced. At the end of the article, simulations prove the superiority of the proposed method.

Integrating blockchain into Internet of Things (IoT) systems can offer many advantages to users and organizations. It provides the IoT network with the capability to distribute computation over many devices and improves the network's security by enhancing information integrity, ensuring accountability, and providing a way to implement better access control. The consensus mechanism is an essential part of any IoT-blockchain platform. In this paper, a novel consensus mechanism based on Proof-of-Authority (PoA) and Proof-of-Work (PoW) is proposed. The security advantages provided by PoW have been realized, and its long confirmation time can be mitigated by combining it with PoA in a single consensus mechanism called Honesty-based Distributed Proof-of-Authority (HDPoA) via scalable work. The measured results of transaction confirmation time and power consumption, and the analyses of security aspects have shown that HDPoA is a suitable and secure protocol for deployment within blockchain-based IoT applications.

The advent of the Internet of Things (IoT) together with its spread in industrial environments have changed pro-duction lines, by dramatically fostering the dynamicity of data sharing and the openness of machines. However, the increased flexibility and openness of the industrial environment (also pushed by the adoption of Edge devices) must not negatively affect the security and safety of production lines and its opera-tional processes. In fact, opening industrial environments towards the Internet and increasing interactions among machines may represent a security threat, if not properly managed. The paper originally proposes the adoption of the Blockchain to securely store in distributed ledgers topology information and access rules, with the primary goal of maximizing the cyber-resiliency of industrial networks. In this manner, it is possible to store and query topology information and security access rules in a completely distributed manner, ensuring data availability even in case a centralized control point is temporarily down or the network partitioned. Moreover, Blockchain consensus algorithms can be used to foster a participative validation of topology information, to reciprocally ensure the identity of interacting machines/nodes, to securely distribute topology information and commands in a privacy-preserving manner, and to trace any past modification in a non-repudiable manner.

Wireless sensors are often deployed in environments where it is difficult for them to discern friend from enemy. An example case is a military tactical scenario, where sensors are deployed to map the location of an item but where some of the nodes have been compromised or where there are other malicious nodes present. In this scenario, sharing data with other network nodes may present a critical security risk to the sensor nodes. Blockchain technology, with its ability to house a secure distributed ledger, offers a possible solution. However, blockchain applications for Wireless Sensor Networks suffer from poor latency in block propagation which in turn decreases throughput and network scalability. Several researchers have proposed solutions for improved network throughput. In this work, a comparison of these existing works is performed leading to a taxonomy of existing algorithms. Characteristics consistently found in algorithms reporting improved throughput are presented and, later, these characteristics are used in the development of a new algorithm for improving throughput. The proposed algorithm utilizes a proof-of- authority consensus algorithm with a node trust-based scheme. The proposed algorithm shows strong results over the base case algorithm and was evaluated with blockchain network simulations of up to 20000 nodes.

The blockchain technology revolution and the use of blockchains in various applications have resulted in many companies and programmers developing and customizing specific fit-for-purpose consensus algorithms. Security and performance are determined by the chosen consensus algorithm; hence, the reliability and security of these algorithms must be assured and tested, which requires an understanding of all the security assumptions that make such algorithms correct and byzantine fault-tolerant.This paper studies the "security ingredients" that enable a given consensus algorithm to achieve safety, liveness, and byzantine fault tolerance (BFT) in both permissioned and permissionless blockchain systems. The key contributions of this paper are the organization of these requirements and a new taxonomy that describes the requirements for security. The CAP Theorem is utilized to explain important tradeoffs between consistency and availability in consensus algorithm design, which are crucial depending on the specific application of a given algorithm. This topic has also been explored previously by De Angelis. However, this paper expands that prior explanation and dilemma of consistency vs. availability and then combines this with Buterin's Trilemma to complete the overall exposition of tradeoffs.

Using the blockchain technology to store the privatedocuments of individuals will help make data more reliable and secure, preventing the loss of data and unauthorized access. The Consensus algorithm along with the hash algorithms maintains the integrity of data simultaneously providing authentication and authorization. The paper incorporates the block chain and the Identity Based Encryption management concept. The Identity based Management system allows the encryption of the user's data as well as their identity and thus preventing them from Identity theft and fraud. These two technologies combined will result in a more secure way of storing the data and protecting the privacy of the user.

Blockchain has received tremendous attention in non-monetary applications including the Internet of Things (IoT) due to its salient features including decentralization, security, auditability, and anonymity. Most conventional blockchains rely on computationally expensive validator selection and consensus algorithms, have limited throughput, and high transaction delays. In this paper, we propose tree-chain a scalable fast blockchain instantiation that introduces two levels of randomization among the validators: i) transaction level where the validator of each transaction is selected randomly based on the most significant characters of the hash function output (known as consensus code), and ii) blockchain level where validator is randomly allocated to a particular consensus code based on the hash of their public key. Tree-chain introduces parallel chain branches where each validator commits the corresponding transactions in a unique ledger.

Zero Trust Model ensures each node is responsible for the approval of the transaction before it gets committed. The data owners can track their data while it’s shared amongst the various data custodians ensuring data security. The consensus algorithm enables the users to trust the network as malicious nodes fail to get approval from all nodes, thereby causing the transaction to be aborted. The use case chosen to demonstrate the proposed consensus algorithm is the college placement system. The algorithm has been extended to implement a diversified, decentralized, automated placement system, wherein the data owner i.e. the student, maintains an immutable certificate vault and the student’s data has been validated by a verifier network i.e. the academic department and placement department. The data transfer from student to companies is recorded as transactions in the distributed ledger or blockchain allowing the data to be tracked by the student.

The ever-increasing number of wireless network systems brought a problem of spectrum congestion leading to slow data communications. All of the radio spectrums are allocated to different users, services and applications. Hence studies have shown that some of those spectrum bands are underutilized while others are congested. Cognitive radio concept has evolved to solve the problem of spectrum congestion by allowing cognitive users to opportunistically utilize the underutilized spectrum while minimizing interference with other users. Byzantine attack is one of the security issues which threaten the successful deployment of this technology. Byzantine attack is compromised cognitive radios which relay falsified data about the availability of the spectrum to other legitimate cognitive radios in the network leading interference. In this paper we are proposing a security measure to thwart the effect caused by these attacks and compared it to Attack-Proof Cooperative Spectrum Sensing.